code: def _make_positive_duplicate_pairs(
      ground_truth: Dict, retrieved: Dict
  ) -> List[Tuple]:
      """
      Given ground_truth and retrieved dictionary, generate all unique positive pairs.
      """
      pairs = []
  
      for mapping in [ground_truth, retrieved]:
          valid_pairs = []
  
          for k, v in mapping.items():
              valid_pairs.extend(list(zip([k] * len(v), v)))
          pairs.append(_get_unique_ordered_tuples(valid_pairs))
  
      return pairs[0], pairs[1]
  
file_path: imagededup/imagededup/handlers/metrics/classification.py
imports: import itertools
  from typing import Dict, List, Tuple
  import numpy
  from sklearn.metrics import classification_report, precision_score, recall_score, precision_recall_fscore_support
  from imagededup.utils.logger import return_logger
label_desc: Use image node_id 3 for calling a global function with example usage: _make_positive_duplicate_pairs(ground_truth, retrieved) and returns: pairs,  pairs